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Executives have an important and ongoing role of setting organizational cultural tone, especially as enterprises embark on various efforts to gain more value from data. Culture has a large role in creating an environment where data-driven decision making becomes the norm. However, fully enabled data-driven decision making is more than just creating a “data” culture or changing individual mindsets and reporting processes. It’s also evolving IT’s mindset and processes around the data itself — including governance — that will fuel that transformation.

Data Culture And Leading ByExample

In a McKinsey piece, ShopRunner CEO Sam Yagan details how culture can be a huge driver in making data an organizational decision cornerstone, highlighting how leaders set the pace: "When workers see the executive team making data-based decisions, it becomes easy for that kind of decision making to flow through the organization."

This is spot-on — setting expectations and cultural tone by walking the walk. With expectations in place, it's logical to expect that the entire organization would be provided the data needed to follow suit. In the organizations I’ve been a part of, I’ve seen the value of leaders both using data and enabling every department with more data. The result is a real mind shift and a proactive culture, where data becomes ingrained in all company operations and drives bottom-line value through improved customer satisfaction and new product offerings.

Leaders setting the example and empowering employees should lead to a data mindset and culture. And yet, even organizations that do this well often fall short in becoming data-driven — why?

You have the culture. What about the data?

Imagine you’re a company where the most senior executives understand the value of a data culture, and you’ve purchased technology to democratize data for every department. But there are still gaps in decision making. How are three different people in the same department coming up with different answers using data? Are you in jeopardy of creating data-driven decision chaos? This is where a somewhat forgotten aspect comes in — data governance.

Although data governance sounds technical, its roots are processes born out of quarterly planning and reporting. Historically many of those needs were at the organizational top-level, requiring strict controls around access and availability. This is where classic data warehouse designs and database management come from — batch, semi-regular needs around important data, segmented and limited in scope and only available to senior-level staff.

But reflect on the trend of democratizing analytical data. The old model of data governance is completely at odds with bringing data to “the masses.” And rest assured, department-level employees are going around IT today to get data any way they can. This leads to the type of analysis chaos described above, based on incomplete, disparate and untrusted data. Consider what this could easily lead to: A retail web team creating a different promotion strategy than the email marketing team, confusing both customers and sales, ultimately leading to abandoned shopping carts during the holiday season when the majority of yearly sales are at stake in a razor-thin margin business.

Modern Governance: Different Roles Leveraging The Same Data

With the dynamic nature of the internet of things (IoT), mobile and social data, organizations can’t treat data with a traditional data governance model. Things move too fast, and to deliver innovative product offerings and solutions before the competition, employees throughout the organization need to leverage data as close to real-time as possible. That doesn’t mean IT should just open the flood gates. An evolved governance model includes the access controls needed to avoid data decision variability and chaos, while still enabling IT to achieve scale and agility by leaving data in data lakes and repositories like the cloud.

It comes down to recognizing not all data can or should be treated the same. You want to enable everyone within reason to work from the same amount of quality data when making decisions across different departments. For example, in most cases you want sales, marketing and web teams to understand reality through the same lens. There are technologies like smart data catalogs and indexes that can provide IT a path forward. Through these tools, IT can design a modern overarching governance process that creates appropriate access to enterprise-ready data, layering in quality assurance with roles and responsibility designations that bring more of the right data, wherever it resides, to the right people at the right time.

IT’s Role In Matching Governance With Data Culture

With an evolved data governance strategy, IT takes on its best and most empowering role — enabling the organization through data. To do so, IT leaders can:

1. Immediately review existing governance processes. Partner with the C-level to evolve these based on company-specific IP and industry compliance needs while balancing the desire to democratize data as much as possible.

2. Educate the masses. Hold internal trainings and webinars on why data controls matter, and how they both protect and enable the organization. This is a big element in how IT creates a data culture. Take the time for department-level training as well. It’s a significant investment, but the alignment will pay off.

3. Consider the role technology and process play. Auditing current data usage across the organization can surface common use cases, helping with effective data-related technology selection such as data catalogs and cloud providers that match user data availability and governance needs.

How data is treated as a resource by IT is as important as the cultural piece to unlocking its full value. Implementing a more modern data governance model helps align the entire organization to drive the business together through data-driven decisions.